Refining computational inference of gene regulatory networks: integrating knockout data within a multi-task framework.

Constructing accurate gene regulatory network s (GRNs), which reflect the dynamic governing process between genes, is critical to understanding the diverse cellular process and unveiling the complexities in biological systems. With the development of computer sciences, computational-based approaches have been applied to the GRNs inference task. However, current methodologies face challenges in effectively utilizing existing topological information and prior knowledge of gene regulatory relationships, hindering the comprehensive understanding and accurate reconstruction of GRNs. In response, we propose a novel graph neural network (GNN)-based Multi-Task Learning framework for GRN reconstruction, namely MTLGRN. Specifically, we first encode the gene promoter sequences and the gene biological features and concatenate the corresponding feature representations. Then, we construct a multi-task learning framework including GRN reconstruction, Gene knockout predict, and Gene expression matrix reconstruction. With joint training, MTLGRN can optimize the gene latent representations by integrating gene knockout information, promoter characteristics, and other biological attributes. Extensive experimental results demonstrate superior performance compared with state-of-the-art baselines on the GRN reconstruction task, efficiently leveraging biological knowledge and comprehensively understanding the gene regulatory relationships. MTLGRN also pioneered attempts to simulate gene knockouts on bulk data by incorporating gene knockout information.

Epigallocatechin-3-Gallate Inhibits Matrix Metalloproteinase-9 and Monocyte Chemotactic Protein-1 Expression Through the 67-κDa Laminin Receptor and the TLR4/MAPK/NF-κB Signalling Pathway in Lipopolysaccharide-Induced Macrophages.

BACKGROUND/AIMS: Epigallocatechin-3-gallate (EGCG), a major catechin found in green tea, has been shown to prevent cardiovascular diseases. Previously, Matrix metalloproteinase-9 (MMP-9), monocyte chemotactic protein-1 (MCP-1) and toll-like receptor 4 (TLR4) were confirmed to play an important role in atherosclerosis and plaque instability. Both TLR4 and its negative regulator, Toll-interacting protein (Tollip), could be mediated by EGCG. The present study aimed to examine the effect of physiological concentration of EGCG (1 µM) on the expression of MMP-9 and MCP-1 in lipopolysaccharide (LPS)-induced macrophages and the potential mechanisms underlying its actions. METHODS: The RAW264.7 cell line was used. Western blot was used to determine MCP-1, TLR4, Tollip, Mitogen-activated protein kinase (MAPK) and Nuclear factor-κB (NF-κB) protein expression. MMP-9 activity was assayed by gelatine zymography. The mRNA expression of MMP-9 and MCP-1 was measured by realtime polymerase chain reaction (RT-PCR). RESULTS: EGCG (1 µM) significantly suppressed the expression of MMP-9 and MCP-1 and inhibited MAPK and NF-κB in LPS-induced macrophages but was blocked by Tollip silencing. The expression of LPS-induced MMP-9 and MCP-1 and the phosphorylation of the ERK1/2, P38 and NF-κB pathway proteins decreased after TLR4 siRNA treatment. Furthermore, EGCG mediated TLR4 and Tollip expression through binding to 67-kDa laminin receptor (67LR). CONCLUSION: The results of our study suggested that EGCG (1 µM) suppresses the TLR4/MAPK/NF-κB signalling pathway, decreases the expression of the plaque instability-mediating cytokines MMP-9 and MCP-1, and might prove to be effective in stabilizing atherosclerotic plaque.

Identification of novel biomarkers, shared molecular signatures and immune cell infiltration in heart and kidney failure by transcriptomics.

Introduction: Heart failure (HF) and kidney failure (KF) are closely related conditions that often coexist, posing a complex clinical challenge. Understanding the shared mechanisms between these two conditions is crucial for developing effective therapies. Methods: This study employed transcriptomic analysis to unveil molecular signatures and novel biomarkers for both HF and KF. A total of 2869 shared differentially expressed genes (DEGs) were identified in patients with HF and KF compared to healthy controls. Functional enrichment analysis was performed to explore the common mechanisms underlying these conditions. A protein-protein interaction (PPI) network was constructed, and machine learning algorithms, including Random Forest (RF), Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO), were used to identify key signature genes. These genes were further analyzed using Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA), with their diagnostic values validated in both training and validation sets. Molecular docking studies were conducted. Additionally, immune cell infiltration and correlation analyses were performed to assess the relationship between immune responses and the identified biomarkers. Results: The functional enrichment analysis indicated that the common mechanisms are associated with cellular homeostasis, cell communication, cellular replication, inflammation, and extracellular matrix (ECM) production, with the PI3K-Akt signaling pathway being notably enriched. The PPI network revealed two key protein clusters related to the cell cycle and inflammation. CDK2 and CCND1 were identified as signature genes for both HF and KF. Their diagnostic value was validated in both training and validation sets. Additionally, docking studies with CDK2 and CCND1 were performed to evaluate potential drug candidates. Immune cell infiltration and correlation analyses highlighted the immune microenvironment, and that CDK2 and CCND1 are associated with immune responses in HF and KF. Discussion: This study identifies CDK2 and CCND1 as novel biomarkers linking cell cycle regulation and inflammation in heart and kidney failure. These findings offer new insights into the molecular mechanisms of HF and KF and present potential targets for diagnosis and therapy.

Volume and function changes of left atrium and left ventricle in patients with ejection fraction preserved heart failure measured by a three dimensional dynamic heart model.

The accurate diagnosis of HFpEF is still challenging and controversial. In this study, we used 3D-DHM technology to compare the differences of cardiac structure and function between HFpEF patients and healthy controls, as well as the differences of two-dimensional and three-dimensional cardiac function in HFpEF patients. Echocardiography with 3D-DHM and conventional two-dimensional (2D) methods were applied to measure the volume and function parameters of left atrium and ventricle of patients with HFpEF and healthy controls. Significant differences of 3D cardiac function indexes including LVESV, 3D-LVEF, ESL, SV, CI, EDmass, LAVmax, LAVmin, LAEF, and LAVI were observed between patients with HFpEF and controls (P < 0.05). However, no significant difference of LVEDV and EDL were observed (P > 0.05). In addition, we found no significant between-group difference in 2D cardiac function indexes such as LVDD and 2D-LVEF (P > 0.05), but the LAD, LVSD, LVPW, IVS, E, E/A, and E/e ' were significantly different between groups (P < 0.05). There was no significant difference between 3D-LVEF and 2D-LVEF in the control group (P > 0.05), while 3D-LVEF in the HFpEF group was lower than 2D-LVEF(P < 0.05). Among the two-dimensional and three-dimensional parameters of HFpEF patients, the parameters related to diastolic function changed more significantly than those of the normal group, and the three-dimensional LVEF of HFpEF patients decreased. The three-dimensional cardiac function parameters analyzed by DHM can provide more information regarding myocardial mechanics.

Hierarchical graph transformer with contrastive learning for gene regulatory network inference.

Gene regulatory networks (GRNs) are crucial for understanding gene regulation and cellular processes. Inferring GRNs helps uncover regulatory pathways, shedding light on the regulation and development of cellular processes. With the rise of high-throughput sequencing and advancements in computational technology, computational models have emerged as cost-effective alternatives to traditional experimental studies. Moreover, the surge in ChIPseq data for TF-DNA binding has catalyzed the development of graph neural network (GNN)-based methods, greatly advancing GRN inference capabilities. However, most existing GNN-based methods suffer from the inability to capture long-distance structural semantic correlations due to transitive interactions. In this paper, we introduce a novel GNN-based model named Hierarchical Graph Transformer with Contrastive Learning for GRN (HGTCGRN) inference. HGTCGRN excels at capturing structural semantics using a hierarchical graph Transformer, which introduces a series of gene family nodes representing gene functions as virtual nodes to interact with nodes in the GRNS. These semanticaware virtual-node embeddings are aggregated to produce node representations with varying emphasis. Additionally, we leverage gene ontology information to construct gene interaction networks for contrastive learning optimization of GRNs. Experimental results demonstrate that HGTCGRN achieves superior performance in GRN inference.

A Comprehensive Survey on Deep Graph Representation Learning.

Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining. Classic graph embedding methods follow the basic idea that the embedding vectors of interconnected nodes in the graph can still maintain a relatively close distance, thereby preserving the structural information between the nodes in the graph. However, this is sub-optimal due to: (i) traditional methods have limited model capacity which limits the learning performance; (ii) existing techniques typically rely on unsupervised learning strategies and fail to couple with the latest learning paradigms; (iii) representation learning and downstream tasks are dependent on each other which should be jointly enhanced. With the remarkable success of deep learning, deep graph representation learning has shown great potential and advantages over shallow (traditional) methods, there exist a large number of deep graph representation learning techniques have been proposed in the past decade, especially graph neural networks. In this survey, we conduct a comprehensive survey on current deep graph representation learning algorithms by proposing a new taxonomy of existing state-of-the-art literature. Specifically, we systematically summarize the essential components of graph representation learning and categorize existing approaches by the ways of graph neural network architectures and the most recent advanced learning paradigms. Moreover, this survey also provides the practical and promising applications of deep graph representation learning. Last but not least, we state new perspectives and suggest challenging directions which deserve further investigations in the future.

ADAMTS12 promotes fibrosis by restructuring extracellular matrix to enable activation of injury-responsive fibroblasts.

Fibrosis represents the uncontrolled replacement of parenchymal tissue with extracellular matrix (ECM) produced by myofibroblasts. While genetic fate-tracing and single-cell RNA-Seq technologies have helped elucidate fibroblast heterogeneity and ontogeny beyond fibroblast to myofibroblast differentiation, newly identified fibroblast populations remain ill defined, with respect to both the molecular cues driving their differentiation and their subsequent role in fibrosis. Using an unbiased approach, we identified the metalloprotease ADAMTS12 as a fibroblast-specific gene that is strongly upregulated during active fibrogenesis in humans and mice. Functional in vivo KO studies in mice confirmed that Adamts12 was critical during fibrogenesis in both heart and kidney. Mechanistically, using a combination of spatial transcriptomics and expression of catalytically active or inactive ADAMTS12, we demonstrated that the active protease of ADAMTS12 shaped ECM composition and cleaved hemicentin 1 (HMCN1) to enable the activation and migration of a distinct injury-responsive fibroblast subset defined by aberrant high JAK/STAT signaling.

GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model.

Deciphering universal gene regulatory mechanisms in diverse organisms holds great potential for advancing our knowledge of fundamental life processes and facilitating clinical applications. However, the traditional research paradigm primarily focuses on individual model organisms and does not integrate various cell types across species. Recent breakthroughs in single-cell sequencing and deep learning techniques present an unprecedented opportunity to address this challenge. In this study, we built an extensive dataset of over 120 million human and mouse single-cell transcriptomes. After data preprocessing, we obtained 101,768,420 single-cell transcriptomes and developed a knowledge-informed cross-species foundation model, named GeneCompass. During pre-training, GeneCompass effectively integrated four types of prior biological knowledge to enhance our understanding of gene regulatory mechanisms in a self-supervised manner. By fine-tuning for multiple downstream tasks, GeneCompass outperformed state-of-the-art models in diverse applications for a single species and unlocked new realms of cross-species biological investigations. We also employed GeneCompass to search for key factors associated with cell fate transition and showed that the predicted candidate genes could successfully induce the differentiation of human embryonic stem cells into the gonadal fate. Overall, GeneCompass demonstrates the advantages of using artificial intelligence technology to decipher universal gene regulatory mechanisms and shows tremendous potential for accelerating the discovery of critical cell fate regulators and candidate drug targets.

Flapless one-knot suture: a novel surgical technique for transscleral fixation of C-loop intraocular lenses.

AIM: To describe a novel suture approach for transscleral fixation of C-loop intraocular lenses (IOL) and to compare the surgical outcomes with the four-haptics posterior chamber (PC)-IOL technique. METHODS: We retrospectively analyzed 16 eyes of 16 patients who underwent transscleral fixation of C-loop PC-IOLs using a flapless one-knot suture technique, which were followed up for longer than 17mo. In this technique, the capsulorless IOL was suspended using a single suture for transscleral fixation of four feet. Then we compared its surgical outcomes and complications with the four-haptics PC-IOLs using the Student's t test and Chi-square test. RESULTS: Sixteen patients of 16 eyes with a mean age of 58.3±10.1y (42-76y) who received transscleral C-loop IOL implantation due to trauma, vitrectomy, or cataract surgery with inadequate capsule support showed improved visual acuity. The difference was not significant between two IOLs except the surgery time (P>0.05). The mean operation times of C-loop IOL surgery was 24.1±1.83min and 31.3±4.47min of the four-haptics PC-IOL method (P<0.0001). In the C-loop IOLs group, there was statistical difference between the preoperative and the postoperative UCVA (logMAR, 1.20±0.50 vs 0.57±0.32, P=0.0003). There was no statistical difference between the preoperative and the postoperative BCVA (logMAR, 0.66±0.46 vs 0.40±0.23, P=0.056). However, there was no statistically significant difference in postoperative UCVA and BCVA between the two IOLs (P>0.05). We did not detect any optic capture, IOL decentration or dislocation, suture exposed, or cystoid macular edema in patients underwent C-loop IOLs surgery. CONCLUSION: The novel flapless one-knot suture technique for transscleral fixation of C-loop IOL is a simple, reliable, and stable technique.

Caffeic Acid Phenethyl Ester Inhibits Ubiquitination and Degradation of p53 and Blocks Cervical Cancer Cell Growth.

BACKGROUND: In high-risk human papillomavirus (HR-HPV)-positive cervical cancer, E6-associated protein (E6AP), an E3 ubiquitin ligase, mediates the ubiquitination and proteasomal degradation of the tumor suppressor p53. Here, we addressed the question of whether caffeic acid phenethyl ester (CAPE), a natural product mainly derived from propolis, can disrupt the interaction between E6AP and p53, inhibit ubiquitination degradation of p53 and exhibit anti-cervical cancer activity. METHODS: The ability of CAPE to inhibit growth and to induce apoptosis was shown in HR-HPV-positive cervical cancer cell lines by performing CCK-8, colony formation and TUNEL assays. Apoptosis-related proteins were tested by western blotting. Coimmunoprecipitation, ubiquitination assay and protein stability assay were carried out to determine whether CAPE can disrupt the E6AP-p53 interaction and inhibit ubiquitination degradation of p53. RESULTS: Our results showed that CAPE inhibits the growth of HR-HPV-positive cervical cancer cells and induces the activation of apoptosis-related pathways. Importantly, CAPE inhibits E6AP expression and disrupts the interaction between E6AP and p53. It inhibits the ubiquitination of p53 and promotes its stabilization. CONCLUSION: In summary, CAPE has a therapeutic effect on HPV-positive malignant cells, so further studies are needed to assess its clinical application.

Platelet-instructed SPP1+ macrophages drive myofibroblast activation in fibrosis in a CXCL4-dependent manner.

Fibrosis represents the common end stage of chronic organ injury independent of the initial insult, destroying tissue architecture and driving organ failure. Here we discover a population of profibrotic macrophages marked by expression of Spp1, Fn1, and Arg1 (termed Spp1 macrophages), which expands after organ injury. Using an unbiased approach, we identify the chemokine (C-X-C motif) ligand 4 (CXCL4) to be among the top upregulated genes during profibrotic Spp1 macrophage differentiation. In vitro and in vivo studies show that loss of Cxcl4 abrogates profibrotic Spp1 macrophage differentiation and ameliorates fibrosis after both heart and kidney injury. Moreover, we find that platelets, the most abundant source of CXCL4 in vivo, drive profibrotic Spp1 macrophage differentiation. Single nuclear RNA sequencing with ligand-receptor interaction analysis reveals that macrophages orchestrate fibroblast activation via Spp1, Fn1, and Sema3 crosstalk. Finally, we confirm that Spp1 macrophages expand in both human chronic kidney disease and heart failure.

[Applications of optical coherence tomography in glaucoma].

As one of the most common irreversible eye diseases, early diagnosis and treatment of glaucoma is vital for a good prognosis but difficult in clinical practice. Optical coherence tomography (OCT) is a non-invasive procedure that can quickly acquire high-resolution cross-sectional images of the ocular structure and is used widely in ophthalmic clinics. In terms of glaucoma, OCT is used to measure the thickness of the retinal nerve fiber layer, the structure of the optic disc, the loss of retinal ganglion cells, the parameters of anterior chamber and anterior chamber angle, the thickness of the iris, the thickness of the lens, the thickness of the choroid, the structure of the filtration bleb and so on. This review summarized the clinical application of OCT in glaucoma diagnosis and the evaluation of glaucoma treatment up till now.

Intraocular pressure 1 year after vitrectomy in eyes without a history of glaucoma or ocular hypertension.

OBJECTIVE: The aim of this study was to investigate the incidence, risk factors, and treatment of elevated intraocular pressure (IOP) 1 year after vitrectomy in eyes without a history of glaucoma or ocular hypertension. PATIENTS AND METHODS: This retrospective study comprised 256 eyes from 256 consecutive patients without a history of glaucoma or ocular hypertension who underwent vitrectomy and were followed up for 1 year. The incidence of elevated IOP at 1 year after vitrectomy was calculated. We compared the characteristics of patients with or without elevated IOP to identify possible risk factors for elevated IOP. The treatments used to control IOP were recorded and analyzed. RESULTS: A total of 50 patients (19.5%) had elevated IOP after vitrectomy at the 1-year follow-up. Tamponade was a significant risk factor for elevated IOP (P<0.05). The cumulative rates of elevated IOP in eyes with air, balanced salt solution, sulfur hexafluoride, perfluoropropane (C3F8), and silicone oil as the tamponade were 0, 10.8%, 5.9%, 19.8%, and 28.4%, respectively (P<0.05). About 68% of cases of elevated IOP occurred within 1 month after vitrectomy. At 1 year after vitrectomy, 29 patients (58.0%) had stopped their IOP-lowering drugs and 21 (42.0%) patients were continuing these drugs. About 65% of ocular hypertension patients who received silicone oil tamponade had not stopped IOP-lowering drugs; this rate was significantly greater than that of ocular hypertension patients who received C3F8 tamponade (18.2%, P<0.05). CONCLUSION: Elevated IOP is a common complication after vitrectomy. Silicone oil tamponade was associated with greater risk of elevated IOP and had long-term effects on IOP. Drugs and surgery were used to control IOP, and some patients required long-term IOP-lowering therapy.

Increased plasma levels of lncRNA H19 and LIPCAR are associated with increased risk of coronary artery disease in a Chinese population.

Recent studies in animal models and humans show that long non-coding RNAs (lncRNAs) are involved in the development of atherosclerosis, which contributes to the pathological foundation of coronary artery disease (CAD). LncRNAs in plasma and serum have been considered as promising novel biomarkers for diagnosis and prognosis of cardiovascular diseases, especially CAD. We here measured the circulating levels of 8 individual lncRNAs which are known to be relevant to atherosclerosis in the plasma samples from 300 patients with CAD and 180 control subjects by using quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) methods. We found that the plasma level of H19 and long intergenic non-coding RNA predicting cardiac remodeling (LIPCAR) were significantly increased in patients with CAD. The area under the receiver operating characteristic curve was 0.631 for H19 and 0.722 for LIPCAR. Multivariate logistic regression analyses indicated that plasma H19 and LIPCAR were independent predictors for CAD, even after adjustment for traditional cardiovascular risk factors. Further studies identified that plasma levels of H19 and LIPCAR were also increased in CAD patients with heart failure compared to those with normal cardiac function. Taken together, our results suggest that increased plasma levels of H19 and LIPCAR are associated with increased risk of CAD and may be considered as novel biomarkers for CAD.

Long Noncoding RNA Kcna2 Antisense RNA Contributes to Ventricular Arrhythmias via Silencing Kcna2 in Rats With Congestive Heart Failure.

BACKGROUND: Congestive heart failure (CHF) is a common cardiovascular disease that is often accompanied by ventricular arrhythmias. The decrease of the slow component of the delayed rectifier potassium current (IKs) in CHF leads to action potential (AP) prolongation, and the IKs is an important contributor to the development of ventricular arrhythmias. However, the molecular mechanisms underlying ventricular arrhythmias are still unknown. METHODS AND RESULTS: Kcna2 and Kcna2 antisense RNA (Kcna2 AS) transcript expression was measured in rat cardiac tissues using quantitative real-time reverse transcription-polymerase chain reaction and Western blotting. There was a 43% reduction in Kcna2 mRNA in the left ventricular myocardium of rats with CHF. Kcna2 knockdown in the heart decreased the IKs and prolonged APs in cardiomyocytes, consistent with the changes observed in heart failure. Conversely, Kcna2 overexpression in the heart significantly attenuated the CHF-induced decreases in the IKs, AP prolongation, and ventricular arrhythmias. Kcna2 AS was upregulated ≈1.7-fold in rats with CHF and with phenylephrine-induced cardiomyocyte hypertrophy. Kcna2 AS inhibition increased the CHF-induced downregulation of Kcna2. Consequently, Kcna2 AS mitigated the decrease in the IKs and the prolongation of APs in vivo and in vitro and reduced ventricular arrhythmias, as detected using electrocardiography. CONCLUSIONS: Ventricular Kcna2 AS expression increases in rats with CHF and contributes to reduced IKs, prolonged APs, and the occurrence of ventricular arrhythmias by silencing Kcna2. Thus, Kcna2 AS may be a new target for the prevention and treatment of ventricular arrhythmias in patients with CHF.

Alcohol consumption and risk of coronary artery disease: A dose-response meta-analysis of prospective studies.

OBJECTIVES: To investigate and quantify the potential dose-response association between alcohol consumption and risk of coronary artery disease (CAD). METHODS: We searched the PubMed database from inception to March 2015 and reviewed the reference list of relevant articles to identify prospective studies assessing the association between alcohol consumption and risk of CAD. Study-specific relative risk (RR) estimates were combined using a random-effects model. Publication bias was estimated using Begg's funnel plot and Egger's regression asymmetry test. The meta-analysis included 18 prospective studies, with a total of 214 340 participants and 7756 CAD cases. The pooled adjusted RRs were 0.62 (95% confidence interval [CI] 0.56-0.68) for highest alcohol consumption amount versus lowest amount. Begg's and Egger's regression tests provided no evidence of substantial publication bias (P = 0.762 for Begg's test and 0.172 for Egger's test). RESULTS: In a dose response analysis, we observed a nonlinear association between alcohol consumption and risk of CAD (P for nonlinearity <0.00). Compared with non-drinkers, the RRs (95% CI) of CAD across levels of alcohol consumption were 0.75 (0.70-0.80) for 12 g/d, 0.70 (0.66-0.75) for 24 g/d, 0.69 (0.64-0.75) for 36 g/d, 0.70 (0.64-0.77) for 60 g/d, 0.74 (0.67-0.83) for 90 g/d, and 0.83 (0.67-1.04) for 135 g/d. CONCLUSIONS: Alcohol consumption in moderation is associated with a reduced risk of CAD with 36 grams/d of alcohol conferring a lower risk than other levels.

Association between Time of Day of Sports-Related Physical Activity and the Onset of Acute Myocardial Infarction in a Chinese Population.

OBJECTIVE: To investigate the association between the time of day of sports-related physical activity and the onset of acute myocardial infarction (AMI) in a coronary artery disease (CAD) population in China. METHODS: Between February 2014 and March 2015, a total of 696 patients from Nanjing, China, who had CAD were studied and divided into two groups (Non-AMI and AMI groups). The work-related activity and sports-related physical activity information were obtained from a self-reporting predesigned patient questionnaire. RESULTS: Sports-related physical activity was associated with a lower risk of the onset of AMI, after adjusting the established and potential confounders, with an adjusted odds ratio (OR) of 0.67 (95% CI, 0.47-0.94) compared with those who did not have any sports-related physical activity. A dose-response relationship was observed for intensity, duration, and frequency of sports-related physical activity. Further stratification analysis revealed that the protective effects of sports-related physical activity were significant in the morning and evening groups, and patients who exercised in the evening were at a lower risk of AMI than those doing sports-related physical activity in the morning. The adjusted ORs for doing sports-related physical activity in the morning and evening groups were 0.60(0.36-0.98) and 0.56(0.37-0.87), respectively, compared with inactivity (all P<0.05). On the occurrence of AMI, doing sports-related physical activity in the evening had an adjusted OR of 0.93 (95% CI, 0.54-1.64, P = 0.824) compared with in the morning group. CONCLUSIONS: Sports-related physical activity is associated with a lower risk of onset of AMI than inactivity in Chinese people. For CAD patients, we suggest they participate in sports-related physical activity of high intensity, long duration, and high frequency. Doing sports-related physical activity in the evening and in the morning have similar benefits on the prevention of the onset of AMI.

Efficacy of equilibrium radionuclide angiography to predict acute response to cardiac resynchronization therapy in patients with heart failure.

OBJECTIVE: To predict the acute response to cardiac resynchronization therapy (CRT) in patients with left ventricular mechanical dyssynchrony using equilibrium radionuclide angiography (ERNA). PATIENTS AND METHODS: A total of 24 consecutive heart failure patients scheduled for CRT were included. ERNA was performed before and within 48 h after pacemaker implantation to calculate both left ventricular (LV) volumes and LV dyssynchrony. LV dyssynchrony was defined as the standard left ventricular phase shift and left ventricular phase standard deviation (LVPS% and LVPSD%). Patients were subsequently divided into acute responders or nonresponders, based on a reduction of at least 15% in LV end-systolic volume immediately after CRT. RESULTS: Fifteen patients (63%) were classified as acute responders. Baseline characteristics were similar between responders and nonresponders except for the LVPS% and LVPSD%, which were larger in responders. Moreover, responders demonstrated a significant reduction of LVPS% and LVPSD% immediately after CRT (from 28.00±2.88 to 17.53±4.94 and 11.20±2.54 to 5.60±1.80, P<0.001), whereas in nonresponders LVPS% and LVPSD% remained unchanged (from 21.44±3.91 to 19.56±4.22% and 6.55±1.51 to 6.22±1.30%, P=NS). Receiver operating characteristic curve analysis revealed that a cut-off value of 25% for LVPS%, a sensitivity of 80% with a specificity of 89% were obtained to predict acute ERNA response to CRT (area under the curve=0.93) and a cut-off value of 8.5% for LVPSD%, a sensitivity of 87% with a specificity of 89% were obtained to predict acute ERNA response to CRT (area under the curve=0.95). CONCLUSION: ERNA is highly predictive for acute response to CRT. ERNA also allows assessment of changes in LV volumes and LV ejection fraction before and after CRT implantation.

Profile of pediatric glaucoma patients in Shanghai Eye, Ear, Nose and Throat Hospital.

BACKGROUND: The extent of our knowledge of the epidemiology of pediatric glaucoma in China is limited. To better characterize the epidemiology of pediatric glaucoma in eastern China, we report the clinical profile, etiologies, and treatment modalities in patients <18 years of age in Shanghai Eye, Ear, Nose and Throat Hospital. METHODS: The medical records of patients presenting glaucoma between January 2003 and December 2010 were retrospectively reviewed. The demographic characteristics, the proportion of different glaucoma subtypes and surgical precedures were collected and analyzed. RESULTS: A total of 1 142 eyes of 734 pediatric patients (500 males) were included. Congenital glaucoma was the leading subtype, accounting for 47.55% of all patients. The ratio of boys to girls was 2.5:1. Patients with congenital glaucoma affecting both eyes accounted for 72.5% of all patients examined. Patients with primary juvenile glaucoma were the second most common group (n = 125, 17.03%). Traumatic glaucoma was the third most common subtype (n = 81, 11.03%). The type of surgery was related to the subtype of glaucoma. CONCLUSIONS: Congenital glaucoma, primary juvenile glaucoma, and traumatic glaucoma are the most prevalent subtypes in pediatric glaucoma patients in Shanghai Eye, Ear, Nose and Throat Hospital. The characteristics of congenital glaucoma in China are similar to those in Western countries.